namemyapp

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the API key requirement and free tier, which is useful, but it does not state whether the operation is read-only, mention rate limits, or describe the return format. This adds some context but leaves significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences with no wasted words. The first sentence states the core purpose, and the second adds the API key prerequisite and pricing. It is appropriately sized and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's purpose, conflict sources, and an important prerequisite, but it does not explain what the tool returns (e.g., a boolean or list). Since there is no output schema, this omission is a notable gap. The description is adequate but not complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides descriptions for both parameters, yielding 100% coverage. The description adds no additional parameter-specific detail beyond what the schema already states, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'check' and clearly identifies the resource (brand name) and the conflict sources (USPTO trademarks, live company homepages, search results). This distinguishes it from sibling tools like check_domain, which focus on domain availability.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies a clear use case—checking brand name conflicts—and does not mention any exclusions. However, it does not explicitly contrast with alternatives or state when not to use this tool, preventing a score of 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full disclosure responsibility. It reveals that a stored payment method will be used, which signals a financial transaction, and states it returns success/failure. However, it does not mention irreversibility or additional costs, though the use of 'stored payment method' is a strong warning.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that front-loads the core action, and the API key requirement is appended as a practical note. No words are wasted, and all information is relevant and directly usable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple, with no output schema, but the description covers the return type. It directly addresses the main risk (payment) and supporting auth requirement. It could mention checking domain availability first, but that is not essential for basic operation. Overall, it is sufficiently complete for an agent to act on.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Both parameters are fully described in the schema (domain and years), achieving 100% coverage. The tool description adds no extra parameter detail beyond what the schema already provides, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Purchase a domain using the stored payment method' with a specific verb and resource, clearly differing from sibling tools like check_domain or buy_link. It also mentions the return value, fully defining the tool's action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implicitly indicates when to use the tool (to purchase a domain) and provides a prerequisite (API key), but it does not explain when to choose this over alternatives or mention any exclusions. The context is clear but lacks explicit comparative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite having no annotations, the description discloses key behavioral traits: always available without API key, generates a URL for browser-based purchase, and does not execute the purchase itself. This adds useful context beyond the schema, though it does not cover potential error conditions or edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the primary purpose, followed by usage guidance. Every word earns its place with no redundancy or tangents.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter URL builder with no output schema, the description fully covers its purpose, usage context, and non-obvious behavioral aspect (no API key required). The agent has enough to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents domain and priceUsd. The tool description adds no additional parameter-level detail, resulting in a baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool builds a one-click purchase URL for buying a domain, with a specific verb and resource. It also differentiates from the sibling tool buy_domain by explaining that the user completes payment in their browser, not via API.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly says 'Use this when the user has decided on a name they like' and describes the hand-off flow. It does not explicitly name alternatives or state when not to use, but the context is clear enough for an agent to decide.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions the API key requirement and URL for obtaining one, but does not disclose other traits such as rate limits, read-only nature, or response format. This is a significant gap for a tool with no annotation safety net.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: one sentence stating the main purpose plus a bracketed note about the API key. Both sentences earn their place, and the main functionality is front-loaded with no redundant wording.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a simple tool with one parameter and no output schema, so the description does not need extensive detail about return values. However, it could benefit from a brief note on the response shape (e.g., availability boolean plus pricing) to fully compensate for the missing output schema. As written, it is adequate but leaves some ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema fully documents the single 'domain' parameter with an example, giving 100% schema description coverage. The description adds no additional parameter semantics, so the baseline of 3 applies as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: checking domain availability and obtaining pricing from the cheapest registrar. This is a specific verb+resource pairing, but it does not explicitly distinguish itself from sibling tools like check_domain_public, so it falls short of a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The only usage guidance is the API key requirement, which is a prerequisite rather than a directive on when to use this tool over alternatives. It does not mention contexts where one would prefer check_domain, check_domain_public, or bulk variants, providing minimal guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden and does well by disclosing rate limiting ('Rate-limited per IP') and the public/no-API-key nature. It also specifies the exact data returned, including a buyUrl, and instructs users to trust that URL. However, it does not mention error handling or behavior on invalid domains, so a perfect score is not warranted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the most important fact ('PUBLIC, NO API KEY required'), then lists return values, usage rules, and the bulk alternative. Every sentence adds value; no fluff or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema, the description is complete: it lists all returned fields, provides clear usage direction, notes rate limiting, and points to a sibling tool for bulk checking. Nothing critical is missing for an agent to select and invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'domain' already has 100% schema description coverage with an example ('taskflow.app'). The tool description does not add additional parameter semantics beyond what the schema provides, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'The one-stop tool for handing a user a domain decision' and enumerates exactly what it returns (availability, prices, registrar, buyUrl). It distinguishes itself from the sibling bulk tool by explicitly naming 'check_domains_public_bulk' for bulk checks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use guidance is given: 'Use this for EVERY candidate before recommending' and 'never invent URLs or prices, always trust the buyUrl this returns.' It also provides an alternative for bulk checks, saying 'For bulk checks (multiple domains in one call), use check_domains_public_bulk.'

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by disclosing the public/no-API-key nature, batch limit of 50, and the return array's fields (availability, price, renewal price, registrar, buyUrl). It also notes performance characteristics. Missing only edge-case or error behavior, but for a read-only check tool, this is strong transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly written sentences front-load the most critical detail (no API key), then explain equivalence, batch size, return structure, and usage preference. No fluff, every sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite lacking an output schema and annotations, the description clearly enumerates the return fields and the single input parameter. It also covers when to use it versus alternatives, making it complete for an agent to select and invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers 100% of parameter semantics with a clear type, maxItems restriction, and example format. The description adds limited new parameter information beyond confirming the 50-domain limit, so baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool checks up to 50 domains in one call, explicitly distinguishing it from the sibling check_domain_public. It specifies the action (check), resource (domains), and bulk scope, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises ALWAYS prefer this over multiple check_domain_public calls when multiple candidates exist, naming the alternative. Also justifies usage with 'faster + fewer rate-limit hits', providing clear context for when to choose this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It usefully discloses access requirements (subscription/purchase and API key) and includes a link for keys. However, it does not explain output structure, side effects, or behavior on failure, leaving gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the main purpose, and the second sentence provides necessary access instructions including a URL. Every element contributes, with no redundant content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having 4 parameters and no output schema, the description only covers prerequisites and high-level outputs. It omits parameter meanings, return format, and any caveats about the generation process, leaving substantial gaps for an agent to operate correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for the four parameters (name, industry, description, includeVisuals), and the description does not explain any of them. The listed brand kit components do not map to inputs, so the description fails to compensate for missing parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a complete brand kit and enumerates its components (essentials, audience, personality, visual identity, voice, imagery, applications, dos-and-donts). This distinguishes it from sibling tools like generate_logo or generate_social_kit by scope, though it does not explicitly name alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a comprehensive brand kit is needed, but provides no explicit guidance on when to choose this tool over siblings. The 'Requires Founder sub or BRAND_KIT purchase' is a prerequisite, not a selection criterion, so usage context is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Since no annotations are provided, the description must carry the burden of behavioral disclosure. It adds worthwhile context about requirements (subscription, API key) and regional awareness, but it does not describe the output format, side effects, or whether the generated documents are returned as text, files, or via links. This leaves a transparency gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concisely structured: the first sentence states the core action and scope, while the second adds essential requirements. It is front-loaded, avoids fluff, and includes a necessary link for API key acquisition. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool that generates documents, the description omits what the output will be (e.g., generated text, files, links) and any notable side effects. It covers input prerequisites and regional scope, but with no output schema, the return value should be explicitly described. Overall, it is adequate but incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 20% (only businessType has a description), and the description provides no parameter details. It does not explain the meaning or format of businessName, regions, websiteUrl, or contactEmail, nor that regions defaults to ['gdpr','ccpa']. The mention of region-aware standards partially hints at the regions parameter, but it is not mapped explicitly.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Generate Privacy Policy, Terms of Service, and Cookie Policy' which specifies a specific resource and verb, and it is easily distinguished from sibling tools like generate_logo or generate_names. The regional scope (GDPR, CCPA, LGPD) further disambiguates the tool from generic document generators.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool (for legal documents) and states explicit prerequisites (Founder sub or LEGAL_KIT purchase, API key). It does not explicitly mention alternatives or when not to use it, but the sibling tools are clearly unrelated to legal docs, so confusion is unlikely.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses the AI-generated nature, output variations ('Returns N variations'), and required access conditions. It does not cover rate limits or error handling, but the core behavioral traits are well communicated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences that front-load the core action in the first sentence and then provide essential prerequisites and API key information in the second. No fluff or redundant content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core function and prerequisites but lacks details on the output format (e.g., how variations are returned) and does not fully explain the nested preferences object. With no output schema and low schema coverage, more detail would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 40%. The description adds context by mentioning palette and typography, which relate to the preferences object, and confirms the count parameter via 'N variations'. However, it does not explicitly explain parameters like slogan or name, relying on self-explanatory names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates AI logo concepts with specific components (icon, palette, typography, layout) for a business. It distinguishes from sibling tools like generate_brand_kit and generate_names by focusing on logo variations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides prerequisites (Founder sub, one-time purchase, free API key) but does not explicitly compare to alternatives like generate_brand_kit or generate_social_kit. Usage is implied by the tool's name and description rather than explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that results are filtered for real-time availability, includes pricing, and requires an API key with a link to obtain one. This goes beyond the structured data, though it doesn't detail error handling or rate limits. Given no annotations, this is valuable context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the main purpose, and includes a concise note about the API key. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the purpose, availability behavior, pricing, and the API key prerequisite. However, without an output schema, it only vaguely describes the return format, leaving some ambiguity about the exact structure of returned names and pricing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage for all four parameters, but the tool description does not add any additional semantics for parameters. It relies entirely on the schema, which is adequate but the description provides no extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it generates brandable business names with real-time domain availability, and emphasizes that returned names are actually available with pricing. This distinguishes it from sibling tools like check_domain or buy_domain.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for generating business names with domain availability, but it does not explicitly mention alternatives or when not to use this tool. There is no guidance distinguishing it from related tools such as check_domain_public or buy_domain.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the transparency burden. It discloses access requirements (subscription/purchase and API key), which is helpful. However, it does not explain what happens on failure, whether the operation is synchronous, or what the response format will be beyond the listed content components. Some behavioral context is added, but significant gaps remain.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose, and every clause adds value (what it does, what it includes, what's required). No fluff or repetition of schema information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 7 parameters, no output schema, and no annotations, the description offers only a high-level output summary and prerequisites. It does not explain how to fill the required parameters, what the generated kit looks like as a response, or any edge-case behavior. This is inadequate for an agent to confidently invoke the tool with correct inputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description provides absolutely no explanation of the meaning or usage of the 7 parameters. The output list does not help infer how to populate fields like `goals`, `platforms`, `voiceTone`, or `targetAudience`. The description fails to compensate for the lack of schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Generate') and clearly states the resource ('social media strategy + content kit') with explicit deliverables (posts, captions, calendar, analytics framework). It is easily distinguished from sibling tools like generate_brand_kit or generate_logo.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool by describing its exact output. It also includes important prerequisites (Founder sub or SOCIAL_MEDIA_KIT purchase, API key). However, it does not explicitly mention alternatives or when not to use it, so it falls short of full guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses the API key requirement, which is a critical authentication need. It does not mention return format or pagination, but as a simple listing operation, the read-only nature is implied by 'list'.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is exactly two sentences: one for purpose and one for the API key requirement with a link. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no parameters and no output schema, the description is fairly complete. It would benefit from stating the return format, but the phrase 'list all domains' adequately conveys the expected outcome. The API key link adds necessary setup context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so the schema provides no parameter meaning. The description appropriately does not discuss parameters, and the baseline for zero parameters is 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'list' with a clear resource 'domains' and scope 'owned by the user', distinguishing it from sibling tools like check_domain or buy_domain. It clearly states the tool's function without being a tautology.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context that this tool is for viewing user-owned domains, and it notes the API key prerequisite. However, it does not explicitly mention when not to use this tool or point to alternatives, so it's a strong but not explicit usage guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description carries the burden of behavioral disclosure. It mentions the need for an API key and the add/update nature of the operation, but it doesn't disclose whether an existing record is overwritten, how long changes take to propagate, or what the API response looks like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the primary action and resource. The API key requirement is clearly bracketed with a direct link, and every sentence adds actionable value without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description is incomplete for an operationally sensitive mutation. It provides use cases and auth context but omits return values, error behavior, overwrite semantics, and validation details, making it insufficient for a tool that modifies DNS records.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low (only 'host' has a built-in description, 20% of parameters). The tool description adds no parameter-specific meaning for 'value', 'type', 'domain', or 'ttl'; it only provides general context about DNS records, leaving the agent to infer format and semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific action ('Add or update') on a specific resource ('a DNS record for a domain'). It also distinguishes itself from sibling domain-related tools by focusing solely on DNS record management rather than domain purchase, checking, or branding.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives practical context on when to use it ('pointing domains to Vercel, Netlify, or email services'). It doesn't explicitly state when not to use it or name alternatives, but the use cases are clear enough for an agent to select it correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.